Measuring user respiration at extremities

ABSTRACT

Systems and methods measure impedance across a user&#39;s chest during respiration to determine a rate of respiration. With AC-modulation contacts separated from impedance-measuring contacts, analog filtering to remove EMI, a bridging capacitor to remove DC noise, and digital filtering to further remove EMI, a user&#39;s respiration may be measured with the AC-modulation contacts and the impedance-measuring contacts placed at user extremities.

CROSS-REFERENCE TO RELATED CASES

The present application is related to International Application NumberPCT/US18/37156, entitled “METHODS AND SYSTEMS FOR PROVIDING A BREATHINGRATE CALIBRATED TO A RESONANCE BREATHING FREQUENCY,” filed on Jun. 12,2018, and to U.S. patent application Ser. No. 16/006,558, entitled“METHODS AND SYSTEMS FOR PROVIDING A BREATHING RATE CALIBRATED TO ARESONANCE BREATHING FREQUENCY,” filed on Jun. 12, 2018 which is acontinuation-in-part of U.S. patent application Ser. No. 15/428,115,entitled “STRESS MANAGEMENT USING BIOFEEDBACK,” filed on Feb. 8, 2017,which claims priority to U.S. Provisional Patent Application No.62/292,450, entitled “WEARABLE APPARATUS WITH BIOFEEDBACK,” filed onFeb. 8, 2016, each of which is hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure relates to the field of sensors, including, moreparticularly, to methods and systems for measuring a user's respiration.

BACKGROUND

It is desirable to be able to measure the respiration rate of a user.For example, heart rate generally increases upon inhalation anddecreases upon exhalation, i.e., some heart rate variation is induced byrespiration. Heart Rate Variability (HRV) is the variation of the timeintervals between heart beats. An increase in HRV is desirable becauseit is indicative of a heart rate that is variable and responsive tophysiological demands. HRV is greatest when individuals breathe at afrequency that is particular to that individual—their resonancebreathing frequency (or “resonance breathing rate”). Respiratory SinusArrhythmia (RSA) occurs when Heart Rate Variability (HRV) is insynchrony with respiration, shown when variability on an ECG isshortened during inspiration (“inhalation”) and prolonged duringexpiration (“exhalation”). Thus, it may be desirable to determine auser's respiration rate and whether that rate is in synchrony with HRV.

Some existing systems and methods for measuring a user's respirationrate rely on a change in the impedance of the user's chest. That changein impedance is caused by two aspects of a user's respiration: a changein the volume of gas in relation to the surrounding tissue; and a changein the electrical path length across the chest that is caused by theexpansion of the chest. The impedance increases as the gas volume andpath length increase. To measure that change, electrodes may be placedon the user on either side of the chest and modulation signals(excitation signals of an alternating current signal at a knownfrequency) may be passed between the electrodes. A base voltage signalis created between the electrodes by the impedance of the user's chestto the AC current when the user has completely exhaled. A respirationvoltage signal is imposed on the base voltage signal by the increase inimpedance caused by the user's respiration. To determine the respirationvoltage signal, the resulting combined voltage signal is demodulated.The respiration frequency is determined from the resulting demodulatedvoltage signal.

FIG. 1 is a prior art circuit diagram for a Texas Instruments ADS1292Rfrom the data sheet for the Texas Instruments ADS1292R, which is alow-power, 2-channel, 24-bit analog-to-digital converter. The datasheetfor a Texas Instruments ADS1292R discloses that a feature of theADS1292R is an integrated respiration impedance measurement. FIG. 1depicts FIG. 56 from the data sheet for the TI ADS1292R. The pinassignments from the ADS1292R are provided in TABLE 1.

TABLE 1 NAME; TERMINAL; FUNCTION; DESCRIPTION AVDD; 12; Supply; Analogsupply AVSS; 13; Supply; Analog ground CLK; 17; Digital input; Masterclock input CLKSEL; 14; Digital input; Master clock select CS; 18;Digital input; Chip select DGND; 24; Supply; Digital ground DIN; 19;Digital input; SPI data in DOUT; 21; Digital output; SPI data out DRDY;22; Digital output; Data ready; active low DVDD; 23; Supply; Digitalpower supply GPIO1/RCLK1; 26; Digital input/output; General-purpose I/O1 or resp clock 1 (ADS1292R) GPIO2/RCLK2; 25; Digital input/output;General-purpose I/O 2 or resp clock 2 (ADS1292R) IN1N⁽¹⁾; 3; Analoginput; Differential analog negative input 1 IN1P⁽¹⁾; 4; Analog input;Differential analog positive input 1 IN2N⁽¹⁾; 5; Analog input;Differential analog negative input 2 IN2P⁽¹⁾; 6; Analog input;Differential analog positive input 2 PGA1N; 1; Analog output; PGA1inverting output PGA1P; 2; Analog output; PGA1 noninverting outputPGA2N; 7; Analog output; PGA2 inverting output PGA2P; 8; Analog output;PGA2 noninverting output PWDN/RESET; 15; Digital input; Power-down orsystem reset; active low RESP_MODN/IN3N⁽¹⁾; 32; Analog input/output;N-side respiration excitation signal for respiration or auxiliary input3N RESP_MODP/IN3P⁽¹⁾; 31; Analog input/output; P-side respirationexcitation signal for respiration or auxiliary input 3P RLDIN/RLDREF;29; Analog input; Right leg drive input to MUX or RLD amplifiernoninverting input; connect to AVDD if not used RLDINV; 28; Analoginput; Right leg drive inverting input; connect to AVDD if not usedRLDOUT; 30; Analog input; Right leg drive output SCLK; 20; Digitalinput; SPI clock START; 16; Digital input; Start conversion VCAP1; 11;—; Analog bypass capacitor VCAP2; 27; —; Analog bypass capacitor VREFN;10; Analog input; Negative reference voltage; must be connected to AVSSVREFP; 9; Analog input/output; Positive reference voltage ⁽¹⁾Connectunused analog inputs to AVDD.

According to the data sheet for the TI ADS1292R, the modulation signalsare supplied by RESP_MODP and RESP_MODN. Exemplary modulationfrequencies are 32 kHz and 64 kHz. Also, according to the data sheet forthe TI ADS1292R, if the Right Arm Lead and Left Arm Lead are intended tomeasure respiration and ECG signals, the two leads are each wired intochannel 1 for respiration signals and channel 2 for ECG signals.Accordingly, FIG. 1 depicts the Right Arm Lead wired into IN2N and IN1Nand the Left Arm Lead wired into IN1P and IN2P. FIG. 1 further depictsthat the Right Arm Lead is also wired into RESP_MODP and that the LeftArm Lead is also wired into RESP_MODP.

However, Applicant determined that the result of the circuit disclosedin the data sheet for the TI ADS1292R was unsatisfactory for measuringrespiration with the contacts placed at a user's extremities. Thus,there is a need for a system and method for measuring a user'srespiration from extremities.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings, in which like referencesindicate similar elements, and in which:

FIG. 1 is a prior art circuit diagram;

FIG. 2 is a circuit diagram illustrating aspects of an embodiment of asystem for measuring the respiration of a user;

FIG. 3 is a circuit diagram further illustrating aspects of theembodiment of a system for measuring the respiration of a user of FIG.2;

FIG. 4 illustrates an embodiment of a method for measuring therespiration of a user;

FIG. 5 illustrates an embodiment of a method for measuring therespiration of a user;

FIG. 6 illustrates an embodiment of a method for measuring therespiration of a user;

FIG. 7 illustrates an embodiment of a method for measuring therespiration of a user;

FIG. 8 is a simplified, exemplary block diagram of an embodiment of asystem for measuring the respiration of a user;

FIG. 9 is an exemplary block diagram of a computing device from thesystem of FIG. 8;

FIG. 10 includes front, back, top, bottom, and right views of anembodiment of a biometric analysis device implementing embodiments ofthe systems and methods disclosed herein; and

FIG. 11 is a perspective view of the biometric analysis device of FIG.10.

DETAILED DESCRIPTION

Applicant desired to measure a user's respiration and ECG signals at theuser's wrist using a wrist-mounted device. For Applicant, the circuitdisclosed in the data sheet for the TI ADS1292R was unsatisfactory formeasuring a user's respiration at this extremity because excessiveelectromagnetic interference (EMI) resulted in noise in the demodulatedsignal. The noise was large enough to cause errors in the determinationof a user's respiration rate. Applicant surmised that the ability of thehuman body to act as an antenna contributed to the excessive EMI andthat attempting to measure respiration from an extremity (i.e., thewrist) further exacerbated the EMI.

Embodiments within disclose improved systems and methods for measuringrespiration that are suitable for measuring respiration at the user'sextremities. The embodiments are discussed using the Texas InstrumentsADS1292R processor, but the ADS1292R is an exemplary electronics deviceand the systems and methods disclosed within may be practiced usingother processors, processor sets, circuitry (both digital and analog),or combinations of these. Thus, “processing electronics” may include oneor more processors, processor sets, circuitry (both digital and analog),or combinations of these. The improvements may include one or more ofthe following: 1) providing user-excitation contacts for the ACmodulation signals where the user-excitation contacts are separate anddistinct from user impedance-measuring contacts; 2) adding a low-passfilter between each user impedance-measuring contact and the respectiveinput into the processing electronics; 3) adding a capacitance betweenthe inputs into the processing electronics; 4) filtering a digitalimpedance signal within the processing electronics to remove a DCcomponent; 5) filtering the digital impedance signal within theprocessing electronics with a low-pass filter to remove further noise;and 6) creating long and short running averages of the impedance signaland, from these, determining that the user is inhaling when the shortrunning average is greater than the long running average and that theuser is exhaling when the short running average is less than the longrunning average.

FIG. 2 and FIG. 3 are circuit diagrams illustrating aspects of anembodiment of a system for measuring a user's respiration fromextremities. FIG. 2 illustrates an embodiment of a modulation circuitry200, which provides user-excitation contacts for the AC modulationsignals that are separate and distinct from user impedance-measuringcontacts that are wired into the respiration channel of processingelectronics 201. It was determined that providing contacts for theAC-modulation signals that are separate from the impedance-measuringcontacts, by itself, significantly reduced noise (e.g., due to EMI) inthe impedance measurement. In FIG. 2, modulation circuitry 200 includesa first user-excitation contact (RL) 202 coupled to a respirationmodulation excitation signal source 206 from electronics 201 (e.g., a TIADS1292R) through a capacitance and a resistance 218. In an embodimentthe capacitance includes a first capacitor 210 and a second capacitor214. In FIG. 2, a second user-excitation contact (LL) 204 is coupled toa respiration modulation excitation signal source 208 through acapacitance and a resistance 220. In an embodiment the capacitanceincludes a first capacitor 212 and a second capacitor 216. In theembodiment of FIG. 2, to provide AC modulation signals that result in animpedance across the user's chest, user-excitation contacts 202 and 204are placed in contact with the skin of a user and on either side of theuser's chest. In an embodiment, a contact may be made, e.g., at eachwrist of the user, or at one wrist and a finger of the opposing arm.Exemplary modulation frequencies for the user-excitation signals include32 kHz and 64 kHz. In an embodiment, resistances 218, 220 may be 40 kΩ,capacitors 210, 212 may be 100 nF, and capacitors 214, 216 may be 2200pF.

FIG. 3 is a circuit diagram further illustrating aspects of theembodiment of a system for measuring a user's respiration fromextremities of FIG. 2. FIG. 3 illustrates circuitry 300, which includescircuitry for measuring the impedance of a user at extremities using afirst user-extremity contact 302 and a second user-extremity contact304. In the embodiment of FIG. 3, to measure the impedance that resultsfrom the AC modulation signals across the user's chest, user-extremitycontacts 302 and 304 are placed in contact with the skin of the user andon either side of the user's chest. In an embodiment, a contact may bemade, e.g., at each wrist of the user, or at one wrist and a finger ofthe opposing arm. FIG. 3 further illustrates that modulation circuitry200 is completely separate and distinct from the impedance-measuringcircuitry between user contacts 302, 304 up to electronics 201. In FIG.3, for measuring impedance, user-extremity contact 302 is coupled to animpedance-measuring input 310 to electronics 201. In this particularembodiment, input 310 is differential analog negative input 1 to the TIADS1292R. Second user-extremity contact 304 is coupled to a second input312 to electronics 201. In this particular embodiment, input 312 isdifferential analog positive input 1 to the TI ADS1292R. Between contact302 and input 310 the circuitry further includes a capacitance, voltagebiasing circuitry, and a low-pass filter 318. In this particularembodiment, the capacitance includes two capacitors 342, 344. Thevoltage biasing circuitry includes two resistors 350, 352, each coupledat one end between the capacitance and low-pass filter 318, withresistor 350 coupled to an analog supply voltage 340 and resistor 352coupled to an analog ground 338. And low-pass filter 318 includes aresistor 330 coupled between the voltage biasing circuitry and input 310and includes a capacitor 332 coupled between resistor 330 and input 310at one end and to ground 338 at the other. Between contact 304 and input312 the circuitry mimics that between contact 302 and input 310, furtherincluding a capacitance, voltage biasing circuitry, and a low-passfilter 320. In this particular embodiment, the capacitance includes twocapacitors 346, 348. The voltage biasing circuitry includes tworesistors 354, 356, each coupled at one end between the capacitance andlow-pass filter 320, with resistor 354 coupled to an analog supplyvoltage 340 and resistor 356 coupled to an analog ground 338. Andlow-pass filter 320 includes a resistor 334 coupled between the voltagebiasing circuitry and input 312 and includes a capacitor 336 coupledbetween resistor 334 and input 312 at one end and to ground 338 at theother.

In the embodiment of FIG. 3, the series capacitance (e.g., capacitors342, 344 and 346, 348) prevents a potential DC current being applied tothe user, with the redundancy of two capacitors protecting against theshort-circuiting of one of the capacitors. The voltage-biasing circuitryestablishes a pre-determined voltage between the two resistors (e.g.,between resistors 350 and 352 and between resistors 354 and 356) that,in this embodiment, is half-way between analog ground 338 and analogsupply voltage 340. Low-pass filters (e.g., low-pass filter 318 and 320)reduce EMI significantly, which contributes to the ability of theembodiment to measure a user's respiration when user-contacts 302, 304are placed on the user's extremities. Embodiments may further include acapacitance between the impedance-sensing inputs to the electronics thatis sized to reduce DC noise. In FIG. 3, such a capacitance isrepresented by a capacitor 358 coupled between inputs 310 and 312.

In an embodiment, the elements of circuit 300 may have the followingvalues: capacitors 342, 346 may be 100 nF; capacitors 344, 348 may be2200 pF; resistors 350, 352, 354, 356 may be 10 MΩ; resistors 330, 334may be 220 kΩ; capacitors 332, 336 may be 22 pF; and capacitor 358 maybe 10 pF.

Thus, in the specific embodiment of FIG. 3, low-pass filters 318, 320have cut-off frequencies 32.9 kHz. In other embodiments, low-passfilters 318, 320 may have other cut-off frequencies and still reduce EMIsufficiently to allow measuring a user's respiration at extremities. Ingeneral, the cut-off frequencies of low-pass filters 318, 320 are chosento narrow the band that must be filtered later by digital filters withinelectronics 201. By narrowing the band, digital filters with betterresponse may be chosen. In an embodiment, the cut-off frequencies may bebetween thirty and thirty-five kilohertz. Thus, in an embodiment,low-pass filters 318, 320 work in combination with signal-processinglogic within electronics 201 to even further reduce EMI because low-passfilters 318, 320 may have cut-off frequencies determined to worksynergistically with signal-processing logic within electronics 201. Inan embodiment, low-pass filters 318, 320 have cut-off frequencies chosento reduce relatively high-frequency EMI, e.g., EMI frequencies of from100 kHz to 1000 kHz, and the digital filtering discussed within isdirected to filtering out substantially lower frequencies, e.g., withcutoff frequencies of from 0.4 Hz to 20 Hz. The hardware low-passfilters 318, 320 filter out most of the noise that comes from the user'sbody to the circuit and the digital filters within electronics 201 maythen be optimized (e.g., with filters that have improved response times)to address board noise of substantially lower frequencies, primarily 24Hz and 60 Hz. The two different low pass filtering systems work togetherto provide a usable respiration signal. Further smoothing of that signalis applied digitally as discussed within, e.g., regarding FIGS. 4-7.

FIG. 3 further illustrates an embodiment of a system for measuring auser's ECG at extremities. For reasons that are similar to those whenmeasuring respiration at extremities, measuring a user's ECG atextremities suffers from increased EMI. In FIG. 3, circuitry 300illustrates an embodiment of ECG-measuring circuitry for measuring theimpedance of a user at extremities using first user-extremity contact302 and second user-extremity contact 304 when user contacts 302, 304are placed in contact with the skin of the user and on either side ofthe user's chest, e.g., at each wrist of the user, or at one wrist and afinger of the opposing arm. In FIG. 3, for measuring a user's ECG, alow-pass filter 314 is coupled between user-extremity contact 302 and aninput 306 to electronics 201. In this particular embodiment, input 306is differential analog negative input 2 to the TI ADS1292R chip.Low-pass filter 314 includes a resistor 322 coupled between user contact302 and input 306 and includes a capacitor 324 coupled between resistor322 and input 306 at one end and to ground 338 at the other. Betweencontact 304 and input 308 the circuitry mimics that between contact 302and input 306, with low-pass filter 316 including a resistor 326 coupledbetween user contact 304 and input 308 and includes a capacitor 328coupled between resistor 326 and input 308 at one end and to ground 338at the other. In an embodiment, low-pass filters 314, 316 have cutofffrequencies that are chosen for anti-aliasing the signals to inputs 306,308, which means their cutoff frequencies are substantially higher thanthose of low-pass filters 318, 320. For example, in an embodiment, thecutoff frequencies of low-pass filters 314, 316 may be 60,000 Hz.

In the embodiment of FIG. 2 and FIG. 3, electronics 201 includesinstructions, which, when contacts 202, 204, 302, 304 are in contactwith a user, cause electronics 201 to determine the impedance betweenuser extremity contacts 302 and 304 and measure the user's respirationrate. The instructions are further discussed regarding FIGS. 4-7.

In an embodiment, electronics 201 may include a first processor and asecond processor. In the embodiment, the first processor includeselectronics contacts 206, 208, 310, 312. The first processor creates adigital impedance signal corresponding to analog impedance data fromuser contacts 302, 304 and provides the digital impedance signal to thesecond processor for subsequent digital signal processing. In anembodiment, the first processor may be a TI ADS1292R analog-to-digitalconverter and the second processor may be an Arm Cortex M4.

FIG. 4 illustrates an embodiment of a method 400 for measuring a user'srespiration from an extremity of the user. In the embodiment, method 400is performed with first and second user contacts on opposing sides ofthe user's chest and the third and fourth user contacts also on opposingsides of the user's chest. In method 400, at step 410, an AC current isprovided between first and second user contacts, causing an impedance todevelop between third and the fourth user contacts. In an embodiment,the contacts may be at a user's extremity, e.g., a user's wrist, or auser's finger. In step 412, the impedance is detected between the thirdand the fourth user contacts, the impedance changing with time due tothe respiration of the user. In step 414, based on the detected changeof the impedance with time, a signal is created that may be used toindicate the respiration rate of the user. The signal is created, inpart, by demodulating the detected impedance to separate thecontribution from the user's respiration from the contribution from theAC modulation signal. In step 416, at least one step from the followingsteps may be performed: the signal is stored in memory; the signal isdisplayed with an electronic device, and the signal is provided to aprocessor for further processing.

It was determined that the impedance measurement of method 400 isimproved (i.e., has less noise) when performed using the embodiments ofthe system described regarding FIG. 2 and FIG. 3. Thus, in anembodiment, steps 410-416 may be performed using an embodiment of asystem described in FIG. 2 and FIG. 3, with the embodiment providing asignal indicating a respiration rate of the user and benefitting fromnoise-reduction contributions provided by embodiments of the systemdescribed regarding FIG. 2 and FIG. 3.

FIG. 4 indicates additional steps, one or more of which may be addedbetween steps 412 and 414 to assist in creating the signal that may beused to indicate the respiration rate of the user. In step 418, animpedance signal may be created from the impedance detected in step 412between the third and the fourth user contacts. In step 420, theimpedance signal may be filtered to remove a DC component, which wasdetermined to exist even after demodulation. In an embodiment, thefiltering to remove a DC component may use a digital filter. In anembodiment, the digital filter may be an infinite impulse response (IIR)filter for DC current with a filtering constant of 0.992. In step 422,the impedance signal may be filtered through a low-pass filter, e.g., tofurther remove EMI. In an embodiment, the low-pass filter may be adigital filter. In an embodiment, the digital low-pass filter may be afinite impulse response (FIR) low-pass filter. In an embodiment, thefilter is chosen to permit frequencies associated with breathing rates,including the particularly desired (or “targeted”) breathing rates. Inan embodiment, the FIR may be a 179^(th) order filter with a gain of 1with 5 dB from 0 to 0.5 Hz and a gain of 0 from 3 Hz and above and with−40 dB attenuation. In an embodiment, the FIR may be a 179^(th) orderfilter with a gain of 1 with 5 dB from 0 to 2 Hz and a gain of 0 from 3Hz and above and with −40 dB attenuation. In an embodiment, theimpedance signal may be filtered by a band-pass filter. In anembodiment, the band-pass filter may be a digital filter. In anembodiment, the digital band-pass filter may be a combination of the IIRfilter for DC current and the FIR low-pass filter.

It was determined that steps 420, 422 are effective in reducing noise inthe impedance measurement, both individually and in combination. Thus,in embodiments, one or both of steps 420, 422 may be performed withsteps 410-416 to provide a signal indicating a respiration rate of theuser and benefitting from noise-reduction contribution from each addedstep.

It was also determined that the benefits in reduced noise provided bysteps 420, 422 were additive to the improvements provided using theembodiments of the system described regarding FIG. 2 and FIG. 3. Thus,in an embodiment, steps 410-416 may be performed using an embodiment ofa system described in FIG. 2 and FIG. 3, with the embodiment of methodand system providing a signal indicating a respiration rate of the userand benefitting from the noise-reduction contributions of step 420 orstep 422 or both.

FIG. 5 illustrates an embodiment of a method 500 for measuring a user'srespiration from extremities. In FIG. 500 describes steps that may beperformed on an impedance signal created from the detected impedancebetween the third and fourth user contacts (as in any of the signalscreated in steps 412, 418, 420, or 422, before they are provided to step414) from which a signal indicting a respiration rate of the user iscreated as in step 414. In step 502, from an impedance signal createdfrom the time-varying impedance detected between the third and fourthuser contacts, a first running average is created over a first runningperiod of time. In step 504, from the same impedance signal of step 502,a second running average is created from a second running period oftime, where the second running period of time is substantially shorterthan the first running period of time. In step 506, the first and secondrunning averages are compared and if the second running average isgreater than the first, it is determined that the user is inhaling.Conversely, in step 508, if the second running average is less that thefirst, it is determined that the user is exhaling. In step 510, thedurations of time between the determinations of when the user isinhaling and exhaling are used to create the signal indicating therespiration rate of the user.

In the embodiment of FIG. 5, the longer running average is taken over aperiod of time with a duration sufficient to determine the averageimpedance of at least one entire wave, i.e., an entire respirationcycle. This effectively provides the center amplitude of the wave (orthe “baseline”). Thus, taking the longer running average is a form of aDC component filtering over and above the IIR filter mentioned earlier.In the embodiment, the shorter running average is taken over a period oftime with a duration that reduces noise without filtering out theimpedance change caused by the user's respiration. In an embodiment, theshorter running average is taken over a 2-second window and the longerrunning average is taken over an 11-second window. The shorter runningaverage is also a form of filtering that is over and above the FIRfilter mentioned earlier.

In embodiments, the methods discussed regarding FIG. 4, or FIG. 5, orboth, may be performed by embodiments of systems discussed regardingFIG. 2 and FIG. 3. In embodiments, the methods of FIG. 4 and FIG. 5 maybe performed by electronics 201 where electronics 201 includes a firstprocessor and a second processor. In these embodiments, the firstprocessor includes electronics contacts 206, 208, 310, 312. The firstprocessor creates a digital impedance signal corresponding to analogimpedance data from user contacts 302, 304 and provides the digitalimpedance signal to the second processor for subsequent digital signalprocessing. In an embodiment, the first processor may be a TI ADS1292Ranalog-to-digital converter and the second processor may be an ArmCortex M4.

In an embodiment, the filtering power of low-pass filters 318, 320 isincreased (or the filtering is “front loaded”), which allows the digitalfiltering described regarding FIG. 4 and FIG. 5 to be fine-tuned anddirected to the remaining noise, thus enhancing the overallnoise-reducing effect of the embodiment over changes to just thecircuits 200, 300 or to just the methods 400, 500.

FIG. 6 illustrates an embodiment of a method 600 for measuring therespiration of a user. The embodiment of FIG. 6 is directed toprocessing that may be performed on a digital signal created from thechanges in impedance caused by a user's respiration, e.g., a digitalsignal created from the impedance from step 412 of method 400, or adigital impedance signal created by electronics 201 and furtherprocessed by software within electronics 201. In FIG. 6, in step 602, adata point indicative of an impedance is received (or taken) at apre-determined frequency, e.g., every 2 ms (i.e., the sampling rate is500 Hz). In step 604, a pre-determined number of data points are summed,e.g., 10 data points may be summed. In step 606, after the data pointsare summed, a filter is implemented that produces a filtered data pointat a predetermined frequency, e.g., every 20 ms (i.e., 50 Hz). In step608, a single-order IIR filtering is performed on the data from step 606to reduce DC noise. In an embodiment, this IIR filter is an IIR filterfrom Texas Instruments included with the TI ADS1292R digital-to-analogconverter. In step, 610, the data stream from step 608 is furtherfiltered using a low-pass FIR filter, e.g., a 179^(th)-order low-passFIR filter with a cut-off frequency of 0.4 Hz. With the data beingsampled at a sufficiently high frequency, e.g., 50 Hz, an FIR filter maybe employed with such a low cut-off frequency without the number of tapsbeing too large for the processor to accommodate (i.e., a lower-orderFIR filter). In step 612, a running average, e.g., a 10-sample runningaverage, is used to smooth the output from the FIR filter and preparethe data for a differentiation filter. In step 614, the data is filteredwith a differentiation filter, e.g., a 5^(th)-order differentiationfilter, which removes high-frequency components from the data. If theoutput of step 614 is larger than 0, then the user is determined to beinhaling. Otherwise the user is exhaling. In step 616, the data isintegrated using a moving window integrator with, e.g., a 50-samplewindow, which at this sampling rate is 1 second of data. The output ofstep 616 may be used to compare the phase angle of the user'srespiration with a target respiration. In an embodiment, the user'srespiration rate may be determined using the time betweenzero-transitions with the data from step 614. In an embodiment, thedetermined user respiration rate may be compared to the changes in theuser's HRV to determine whether the user's HRV is in synchrony with theuser's respiration (i.e., whether the user is in RSA). In an embodiment,the signal from step 412 may be processed as described in steps 608-614with the resulting signal supplied to step 414. In an embodiment, thesignal from step 412 may be processed as described in steps 602-614 withthe resulting signal supplied to step 414.

FIG. 7 illustrates an embodiment of a method 700 for measuring therespiration of a user that corrects for (or “cancels out”) skewing thatmight be induced due the user's skin varying in a level of moistnesswhile respiration is being measured. Method 700 builds on method 600. Instep 702, the zeroes in the differentiation-filtered output of step 614are used to find the local minimums and maximums of the user'srespiration. In step 704, a running average is created from the localminimums and a running average is created from the local maximums. Instep 706, the output of step 614 is rescaled by dividing positive valuesby the running average of the local maximums and by dividing negativevalues by the running average of the local minimums. The result of step706 is that the respiration data will be a scaled wave that ranges from−1 to 1, where positive values indicate the user is inhaling andnegative values indicate the user is exhaling. With the respiration databeing maintained between −1 and 1, the skew is eliminated. In anembodiment, the running average of step 704 is constructed using thelast ten (10) local minimums and last ten (10) local maximums.

FIG. 8 is a simplified, exemplary block diagram of an embodiment of asystem 800 for implementing the embodiments of systems and methodsdisclosed herein. System 800 may include a number of sensors, e.g., arespiration rate sensor 805 (e.g., as described within this disclosure)and a heart rate sensor 810 (e.g., as described within this disclosure),for developing data regarding a user. Sensors 805, 810, and 820 are incommunication with a computing device 815. Computing device 815 mayfurther be in control of a haptic device 825 and a buzzer or speaker(not shown) for communicating with the user. System 800 may be referredto as a Biometric Analysis Device.

Respiration rate sensor 805 may be an impedance-based sensor asdiscussed within this specification. Heart rate sensor 810 may be, e.g.,a plurality of sensors sufficient to produce an electrocardiogram (ECG,as discussed within), a chest-mounted device, or a wrist-mounted device,so long as the device provides heart rate data with sufficient accuracyand precision. Sensor 820 is representative of additional sensors thatmay be included, such as sensors for determining galvanic skin response,temperature, blood pressure, hydration, sleep, exercise activity, brainactivity, nutrient levels, or blood analysis. Sensors 805, 810, and 820may supply data to computing device 815 via communication links 830.

Computing device 815 may include a user interface and software, whichmay implement the steps of the methods disclosed within. Computingdevice 815 may receive data from sensors 805, 810, and 820, viacommunication links 830, which may be hardwire links, optical links,satellite or other wireless communications links, wave propagationlinks, or any other mechanisms for communication of information. Variouscommunication protocols may be used to facilitate communication betweenthe various components shown in FIG. 8. Distributed system 800 in FIG. 8is merely illustrative of an embodiment and does not limit the scope ofthe systems and methods as recited in the claims. In an embodiment, theelements of system 800 are incorporated into a single, wearableBiometric Analysis Device (e.g., as described regarding FIGS. 10 and11). One of ordinary skill in the art would recognize other variations,modifications, and alternatives. For example, more than one computingdevice 815 may be employed. As another example, sensors 805, 810, and820 may be coupled to computing device 815 via a communication network(not shown) or via some other server system.

Computing device 815 may be responsible for receiving data from sensors805, 810, and 820, performing processing required to implement the stepsof the methods, and for interfacing with the user. In some embodiments,computing device 815 may receive processed data from sensors 805, 810,and 820. In some embodiments, the processing required is performed bycomputing device 815. In such embodiments, computing device 815 runs anapplication for receiving user data, performing the steps of the method,and interacting with the user. In other embodiments, computing device815 may be in communication with a server, which performs the requiredprocessing, with computing device 815 being an intermediary incommunications between the user and the processing server.

System 800 enables users to access and query information developed bythe disclosed methods. Some example computing devices 815 includedesktop computers, portable electronic devices (e.g., mobilecommunication devices, smartphones, tablet computers, laptops) such asthe Samsung Galaxy Tab®, Google Nexus devices, Amazon Kindle®, KindleFire®, Apple iPhone®, the Apple iPad®, Microsoft Surface®, the PalmPre™, or any device running the Apple iOS®, Android® OS, Google Chrome®OS, Symbian OS®, Windows Mobile® OS, Windows Phone, BlackBerry® OS,Embedded Linux, Tizen, Sailfish, webOS, Palm OS® or Palm Web OS®; orwearable devices such as smart watches, smart fitness or medical bands,and smart glasses.

FIG. 9 is an exemplary block diagram of a computing device 815 from thesystem of FIG. 8. In an embodiment, a user interfaces with the systemthrough computing device 815, which also receives data and performs thecomputational steps of the embodiments. Computing device 815 may includea display, screen, or monitor 905, housing 910, input device 915,sensors 950, and a security application 945. Housing 910 houses familiarcomputer components, some of which are not shown, such as a processor920, memory 925, battery 930, speaker, transceiver, antenna 935,microphone, ports, jacks, connectors, camera, input/output (I/O)controller, display adapter, network interface, mass storage devices940, and the like. In an embodiment, sensors 950 may include sensors805, 810, and 820 incorporated into computing device 815, and hapticdevice 825 may also be incorporated into device 815. In an embodiment,housing 910 is the housing of the wearable biometric analysis device1000 of FIGS. 10 and 11.

Input device 915 may also include a touchscreen (e.g., resistive,surface acoustic wave, capacitive sensing, infrared, optical imaging,dispersive signal, or acoustic pulse recognition), keyboard (e.g.,electronic keyboard or physical keyboard), buttons, switches, stylus, orcombinations of these.

Display 904 may include dedicated LEDs for providing directing signalsand feedback to a user.

Mass storage devices 940 may include flash and other nonvolatilesolid-state storage or solid-state drive (SSD), such as a flash drive,flash memory, or USB flash drive. Other examples of mass storage includemass disk drives, floppy disks, magnetic disks, optical disks,magneto-optical disks, fixed disks, hard disks, CD-ROMs, recordable CDs,DVDs, recordable DVDs (e.g., DVD-R, DVD+R, DVD-RW, DVD+RW, HD-DVD, orBlu-ray Disc), battery-backed-up volatile memory, tape storage, reader,and other similar media, and combinations of these.

System 900 may also be used with computer systems having configurationsthat are different from computing device 815, e.g., with additional orfewer subsystems. For example, a computer system could include more thanone processor (i.e., a multiprocessor system, which may permit parallelprocessing of information) or a system may include a cache memory. Thecomputing device 815 shown in FIG. 9 is but an example of a computersystem suitable for use. For example, in a specific implementation,computing device 815 is a wrist-mounted Biometric Analysis Device incommunication with or incorporating the sensors of FIG. 9. An example ofsuch a Biometric Analysis Device is discussed regarding device 1000 ofFIGS. 10 and 11. Other configurations of subsystems suitable for usewill be readily apparent to one of ordinary skill in the art. In otherspecific implementations, computing device 815 is a mobile communicationdevice such as a smartphone or tablet computer. Some specific examplesof smartphones include the Droid Incredible and Google Nexus One®,provided by HTC Corporation, the iPhone® or iPad®, both provided byApple, BlackBerry Z10 provided by BlackBerry (formerly Research InMotion), and many others. The Biometric Analysis Device may be a laptopor a netbook. In another specific implementation, the Biometric AnalysisDevice is a non-portable computing device such as a desktop computer orworkstation.

In an embodiment, system 900 may be incorporated into a single module.The module may have four user contacts (or “electrodes”) placed to allowa user to make contact with two contacts with one user extremity andwith the other two contacts with the other user extremity. This modulecan be contained within numerous types of wristband straps (leather,etc.) and form factors (such as key chain, steering wheel cover, etc.).The module, or the strap or other form factor, may also include a smallOLED display to display the current time. The module may executesoftware that performs an embodiment of the method. Accordingly, themodule may provide the user with feedback, e.g., an indication of theuser's respiration rate or heart rate or both.

FIG. 10 includes front, back, top, bottom, and right views of anembodiment of a wearable biometric analysis device 1000 for implementingembodiments of the methods disclosed within. Components and capabilitiesof biometric analysis device 1000 are also described with reference toFIGS. 2-9. Biometric Analysis Device 1000 includes a computing device1005 and a sensor coupled to electrical contacts 1010, 1012, 1014, 1016that acquire data that may be used to provide a measure of the user'srespiration rate as discussed above. Computing device 1005 processesbiometric data measured by the sensor(s) and produces feedbackcorrelating to the processed biometric data. By continuously monitoringone or more biometric values, the user may respond to the data receivedand modify their behavior or activity to improve health and performance.The biometric analysis device 1000 thereby provides feedback by sensingand reporting a biometric value measured by the sensor to the user inreal time. In an embodiment, contacts 1010, 1012, 1014, 1016 providedata to a TI ADS1292R sensor. As such, Biometric Analysis Device 1000may be equipped with both a respiration rate sensor and a heart ratesensor. Computing device 1005 is in communication with the sensor orsensors associated with contacts 1010, 1012, 1014, 1016. Computingdevice 1005 may also control a haptic device (not shown) forcommunicating with the user. Computing device 1005 may include a display1015, a user interface, and software, for implementing the steps of themethods disclosed within. In an embodiment, contacts 1010 and 1012 maycorrespond to contacts 202 and 302 as described above, and contacts 1014and 1016 may correspond to contacts 204 and 304 as described above. Inthe embodiment, a method for determining the user's respiration rateincludes the user placing device 1000 on one of the user's wrists suchthat contacts 1010, 1012 are in contact with the user's wrist. Then, theuser brings contacts 1014, 1016 in contact with another part of theuser's body such as one or more fingers on the user's opposing hand. Inother words, the user touches contacts 1014, 1016 to a part of theuser's body so that some or all of the user's chest is between contactpairs 1010, 1012 and 1014, 1016 (the circuits are described withreference to FIGS. 2 and 3 and contact pairs 202, 302 and 204, 304). Inan embodiment, the part of the user's body may be a finger or other partof the opposing arm, may be a section of the user's torso, or may be asection of a leg of the user. With both contact pairs 1010, 1012 and1014, 1016 in such contact with the user, the device then determines theuser's respiration rate, heart rate, or both according to the methodsdescribed within.

Computing device 1005 may receive data from sensors 1010, 1012, 1014,1016, perform processing required to implement the steps of the methodsdisclosed within, and provide a user interface via display 1015. In someembodiments, all processing required is performed by computing device1005. In such embodiments, computing device 1005 executes instructionsfor receiving user data, performing the steps of the method, andinteracting with the user. In other embodiments, computing device 1005may be in communication with a server, which performs part of therequired processing, with computing device 1005 being an intermediary incommunications between the user and the processing server.

As illustrated, Biometric Analysis Device 1000 generally comprises aband 1020 configured to be worn about a wrist of the user. The band 1020includes an adjustment mechanism 1025, for adjusting a circumference ofthe band 1020. A user can thus select, using adjustment mechanism 1025,a particular size for positioning band 1020 about the user's wrist. Avisual indication, e.g., for feedback, may be provided by display 1015.In an embodiment, visual indicators may be further be positioned on theband 1020 to provide visual signals to the user. Sensor(s) associatedwith contacts 1010, 1012, 1014, 1016 may be configured to be activatedby computing device 1005. In an embodiment, additional sensors, e.g., atemperature sensor or a galvanic response sensor, may be provided toprovide more user data for determining vagal tone. In an embodiment, oneor more translucent windows may be positioned about the band 1020 totransmit light from one or more indicators positioned with the band1020.

Biometric analysis device 1000, in one embodiment, is used measure auser's respiration rate. Accordingly, the biometric analysis device 1000may provide the user with real-time, personal biofeedback. In anembodiment, device 1000 may measure both a user's respiration rate andheart rate and provide feedback regarding one or both. The biofeedbackmay allow the user to learn about the user's personal physiologicalstate and physiological responses. As a result, the biofeedback providedto the user (by, e.g., one or more of display 1015, or haptic device, orspeaker) may enable the user to self-regulate the user's activity andbehavior to improve the user's performance or health. In an embodiment,device 1000 may provide a user with feedback (e.g., a vibration patternof frequency, duration, and magnitude) selected to encourage a desiredbehavior. In an embodiment, biometric analysis device 1000 is configuredto provide the user with feedback with reference to previously-collectedbiometric data, such as respiration rate or heart rate variability. Thebiometric analysis device 1000 may emit vibrations based on the user'sactual respiration rate, or a target respiration rate. For example, avisual indication from, e.g., display 1015, may be provided andconfigured to emit different colors based on when the user is supposedto inhale and exhale for deep breathing relaxation techniques. The usermay also be capable of changing the breathing intervals. The visualindication and breathing intervals may be enabled and adjusted throughthe user interface.

FIG. 11 is a perspective view of the biometric analysis device of FIG.10.

FIGS. 10 and 11 illustrate one example embodiment of a wearablebiometric analysis device 1000 that is configured to measure therespiration rate of a user. In one embodiment, biometric analysis device1000 can include each of the elements of system 800 of FIG. 8 and FIG.9. In other embodiments, biometric analysis device 1000 can includeother elements that function with biometric analysis device 1000 toprovide biometric measurement and analysis to assist a user with stressmanagement.

In the description above and throughout, numerous specific details areset forth in order to provide a thorough understanding of an embodimentof this disclosure. It will be evident, however, to one of ordinaryskill in the art, that an embodiment may be practiced without thesespecific details. In other instances, well-known structures and devicesare shown in block diagram form to facilitate explanation. Thedescription of the preferred embodiments is not intended to limit thescope of the claims appended hereto. Further, in the methods disclosedherein, various steps are disclosed illustrating some of the functionsof an embodiment. These steps are merely examples and are not meant tobe limiting in any way. Other steps and functions may be contemplatedwithout departing from this disclosure or the scope of an embodiment.

1.-10. (canceled)
 11. A wrist-mountable device including: electronicsincluding a processor with memory and instructions; a first user contactdisposed on a first side of the device; a second user contact disposedon a second side of the device; a third user contact disposed on thefirst side of the device; and a fourth user contact disposed on thesecond side of the device or a third side of the device, wherein: whenthe device is mounted on the user, and the first side of the device ispositioned against a first arm of the user, the first user contact andthe third user contact make contact with the first arm of the user andare not accessible by a second arm of the user, and the second usercontact and fourth user contact are accessible by the second arm; andthe instructions, when executed by the processor with the first andthird user contacts in contact with the first arm and the second andfourth user contacts in contact with the second arm, cause theelectronics to: provide an AC current between the first and second usercontacts, the AC current causing an impedance to develop between thethird and the fourth user contacts; detect the impedance between thethird and the fourth user contacts, the impedance changing with time;and based on the detected change of the impedance with time, create asignal indicating a respiration rate of the user.
 12. The device ofclaim 11, wherein the instructions further cause the electronics to:create an impedance signal from the detected impedance between the thirdand the fourth user contacts; filter the impedance signal to remove a DCcomponent; and filter the impedance signal through a low-pass filter.13. The device of claim 12, wherein the low-pass filter has a cut-offfrequency of two hertz and the attenuation is minus forty decibels perdecade above three hertz. 14.-19. (canceled)
 20. The device of claim 11,wherein the electronics includes a Texas Instruments ADS1292Ranalog-to-digital converter and an Arm Cortex M4 processor and firstthrough fourth electronics contacts are on the Texas InstrumentsADS1292R analog-to-digital converter.
 21. A method comprising: providinga user with a wrist-mountable device including: electronics including aprocessor with memory and instructions; a first user contact disposed ona first side of the device; a second user contact disposed on a secondside of the device; a third user contact disposed on the first side ofthe device; and a fourth user contact disposed on the second side of thedevice or a third side of the device, wherein: when the device ismounted on the user, and the first side of the device is positionedagainst a first arm of the user, the first user contact and the thirduser contact make contact with the first arm of the user and are notaccessible by a second arm of the user, and the second user contact andfourth user contact are accessible by the second arm; bringing the firstand third user contacts in contact with the first arm and the second andfourth user contacts in contact with the second arm: providing, by thewrist-mountable device, an AC current between the first and second usercontacts, the AC current causing an impedance to develop between thethird and the fourth user contacts; detecting, by the wrist-mountabledevice, the impedance between the third and the fourth user contacts,the impedance changing with time; and based on the detected change ofthe impedance with time, creating, by the wrist-mountable device, asignal indicating a respiration rate of the user.
 22. The method ofclaim 21, further including: creating, by the wrist-mountable device, animpedance signal from the detected impedance between the third and thefourth user contacts; filtering, by the wrist-mountable device, theimpedance signal to remove a DC component; and filtering, by thewrist-mountable device, the impedance signal through a low-pass filter.23. The method of claim 22, wherein the low-pass filter has a cut-offfrequency of two hertz and the attenuation is minus forty decibels perdecade above three hertz.
 24. The method of claim 21, wherein theelectronics includes a Texas Instruments ADS1292R analog-to-digitalconverter and an Arm Cortex M4 processor and first through fourthelectronics contacts are on the Texas Instruments ADS1292Ranalog-to-digital converter.
 25. A non-transitory computer-readablemedium encoded with a plurality of instructions which, when executed bya processor of a wrist-mounted device including: electronics includingthe processor and memory; a first user contact disposed on a first sideof the device; a second user contact disposed on a second side of thedevice; a third user contact disposed on the first side of the device;and a fourth user contact disposed on the second side of the device or athird side of the device, wherein: when the device is mounted on theuser, and the first side of the device is positioned against a first armof the user, the first user contact and the third user contact makecontact with the first arm of the user and are not accessible by asecond arm of the user, and the second user contact and fourth usercontact are accessible by the second arm; and with the first and thirduser contacts in contact with the first arm and the second and fourthuser contacts in contact with the second arm, cause the wrist-mounteddevice to: provide an AC current between the first and second usercontacts, the AC current causing an impedance to develop between thethird and the fourth user contacts; detect the impedance between thethird and the fourth user contacts, the impedance changing with time;and based on the detected change of the impedance with time, create asignal indicating a respiration rate of the user.
 26. Thecomputer-readable medium of claim 25, the instructions further causingthe wrist-mounted device to: create an impedance signal from thedetected impedance between the third and the fourth user contacts;filter the impedance signal to remove a DC component; and filter theimpedance signal through a low-pass filter.
 27. The computer-readablemedium of claim 26, wherein the low-pass filter has a cut-off frequencyof two hertz and the attenuation is minus forty decibels per decadeabove three hertz.
 28. The computer-readable medium of claim 25, whereinthe electronics includes a Texas Instruments ADS1292R analog-to-digitalconverter and an Arm Cortex M4 processor and first through fourthelectronics contacts are on the Texas Instruments ADS1292Ranalog-to-digital converter.
 29. The device of claim 11, wherein thesecond user contact and fourth user contact being accessible by thesecond arm includes the second user contact and fourth user contactbeing accessible by one or more fingers on a hand of the second arm. 30.The method of claim 21, wherein the second user contact and fourth usercontact being accessible by the second arm includes the second usercontact and fourth user contact being accessible by one or more fingerson a hand of the second arm.
 31. The computer-readable medium of claim25, wherein the second user contact and fourth user contact beingaccessible by the second arm includes the second user contact and fourthuser contact being accessible by one or more fingers on a hand of thesecond arm.